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Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing.
- Source :
-
Small (Weinheim an der Bergstrasse, Germany) [Small] 2025 Feb 05, pp. e2411585. Date of Electronic Publication: 2025 Feb 05. - Publication Year :
- 2025
- Publisher :
- Ahead of Print
-
Abstract
- Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, high-sensitivity detection of cardiac troponin I (cTnI) is demonstrated through innovations in chemiluminescence-based sensing, imaging, and deep learning-driven analysis. This chemiluminescence vertical flow assay (CL-VFA) enables rapid, low-cost, and precise quantification of cTnI, a key cardiac protein for assessing heart muscle damage and myocardial infarction. The CL-VFA integrates a user-friendly chemiluminescent paper-based sensor, a polymerized enzyme-based conjugate, a portable high-performance CL reader, and a neural network-based cTnI concentration inference algorithm. The CL-VFA measures cTnI over a broad dynamic range covering six orders of magnitude and operates with 50 µL of serum per test, delivering results in 25 min. This system achieves a detection limit of 0.16 pg mL <superscript>-1</superscript> with an average coefficient of variation under 15%, surpassing traditional benchtop analyzers in sensitivity by an order of magnitude. In blinded validation, the computational CL-VFA accurately measures cTnI concentrations in patient samples, demonstrating a robust correlation against a clinical-grade FDA-cleared analyzer. These results highlight the potential of CL-VFA as a robust diagnostic tool for accessible, rapid cardiac biomarker testing that meets the needs of diverse healthcare settings, from emergency care to underserved regions.<br /> (© 2025 The Author(s). Small published by Wiley‐VCH GmbH.)
Details
- Language :
- English
- ISSN :
- 1613-6829
- Database :
- MEDLINE
- Journal :
- Small (Weinheim an der Bergstrasse, Germany)
- Publication Type :
- Academic Journal
- Accession number :
- 39910838
- Full Text :
- https://doi.org/10.1002/smll.202411585